Weighted random sampling and reconstruction in general multivariate trigonometric polynomial spaces

The set of sampling and reconstruction in trigonometric polynomial spaces will play an important role in signal processing. However, in many applications, the frequencies in trigonometric polynomial spaces are not all integers. In this paper, we consider the problem of weighted random sampling and reconstruction of functions in general multivariate trigonometric polynomial spaces. The sampling set is randomly selected on a bounded cube with a probability distribution. We obtain that with overwhelming probability, the sampling inequality holds and the explicit reconstruction formula succeeds for all functions in the general multivariate trigonometric polynomial spaces when the sampling size is sufficiently large.

Strategy of efficient estimation of soil organic content at the local scale based on the national spectral database

The aim of this paper was to compare the prediction performance of three strategies: general global Partial least squares regression (PLSR) using CSSL with and without spiking samples, memory-based learning (MBL) using CSSL with and without spiking samples and general PLSR using only spiking samples to predict soil organic matter in the target area. When using spiked subsets, we also investigated the prediction performance of the extra-weighted subsets. A series of spiking subsets randomly selected from the total spiking samples were selected by conditioned Latin hypercube sampling (cLHS) from the target sites. We calculated the mean squared Euclidean distance (msd) of different spiking subsets with the distribution density function of their vis–NIR spectra only and statistically inferred the optimal sampling set size to be 30. Our study showed that when the number of spiking were lower than 30, the predicted accuracy derived from global PLSR using CSSL spiked with and without extra-weighted samples was greater than the predicted accuracy derived from the general PLSR using the corresponding number of spiking samples only (RMSE 5.57–5.98 v.s. RMSE 6.76). Global PLSR using CSSL spiked with the statistically optimal local samples can achieve higher predicted performance (with a mean RMSE of 5.75). MBL spiked with five extra-weighted optimal spiking samples achieved the best accuracy with an RMSE of 3.98, an R2 of 0.70, a bias of 0.04 and an LCCC of 0.81. The msd is a simple and effective method to determine an adequate spiking size using only vis–NIR data.

Integrated Method for Road Extraction: Deep Convolutional Neural Network Based on Shape Features and Images

As a significant application in RS images, road detection is still a challenging task due to the presence of complex surroundings and multiple false objects. To achieve a satisfying result, a road detection method based on residual learning and saliency sampling is developed in this paper. First, a multistrapdown module is designed with double residual learning blocks that have low computational complexity and time consumption. Second, to improve the classification accuracy and learning ability of the method, a saliency sampling set is established by fusing brightness, orientation and texture maps. The sampling set is imported and merged into the model through the pooling layer. Finally, the cross entropy loss function is carried out in a Softmax classifier. Extensive experiments show that our proposed integrated method is much better than the state-of-the art methods in detection accuracy.

VM-ADCP backscatter data management using QGIS

<p>VM-ADCP (Vessel Mounted Acoustic Doppler Current Profiler) are regularly operating on board of several research vessels with the aim of providing 3-D ocean currents fields. Along with ocean currents, these instruments also measure acoustic backscatter profile on a known frequency, that can be of great advantages for other environmental investigations such as the zooplankton migrations. The presence of zooplankton can be detected by a variation of acoustic backscatter changing  with the depth at a periodic (diurnal or semidiurnal) variability, related to the vertical  migration of these organisms. GIS has proven to be a powerful tool to manage the huge amount of VM-ADCP backscatter data obtained during the oceanographic campaigns. Moreover, this allows to extract relevant information on zooplankton distribution and abundance, even when the monitoring strategy of the experiment does not completely meet the temporal and spatial resolution required for these studies. The application here described has been developed on QGIS and tested on the Ligurian Sea (Mediterranean Sea). In order to obtain the comparability of data from instruments operating at different frequencies and sampling set-up, echo intensity data are converted into volume backscatter strength and corrected for the slant-range. Using high-resolution bathymetry rasters acquired and processed by the Italian Hydrographic Institute, allows to discard the anomalous high backscatter values due to presence of the bottom. Another advantage of the GIS is the possibility to easily identify night-collected data from the daily ones and their spatial distribution, as well as those from the surface and the deeper layer. All the possible combinations can be then visualised and analysed.</p>

The effect of tax socialization, superior service, and service quality on taxpayers’ satisfaction and compliance

The impact of valuable services for taxpayers will increase the awareness and compliance of taxpayers. This study aims to explore whether there is a direct or indirect effect on the effectiveness of tax socialization, superior service products, and the quality of services to taxpayer satisfaction and taxpayer compliance. The study was conducted at the East Java Provincial Revenue Agency through 48 motorized vehicle service units, with purposive sampling set at 426 respondents in the Gresik, Bangkalan, Mojokerto, Surabaya, Sidoarjo and Lamongan regions with 2014 ownership of motorized vehicle years. With SEM analysis the results of the study stated that there were significant direct or indirect effectiveness of tax socialization, superior service products, and quality of service to taxpayers' satisfaction and compliance as a mediating variable. The implication is that if the Central Tax Ofiice conducts a tax socialization effective on target, provide superior service products, and quality of services in all districts / cities in East Java Province, they can make taxpayeers obedient by voluntarily paying motor vehicle taxes on time.